I’m a computational social scientist working mainly in the areas of Scientometrics and Science of Science.

I’m a python enjoyer and I work a lot with NLP, topic modeling and textual data in general. But I’m also interested in (social) network analysis and agent-based modeling. Also, my favourite flavour of statistics is Bayesian (applied both via Stan and PyMC).

I got my PhD in Economic Sociology and Public Administration via a cotutelle agreement between the University of Milan (Italy) and the University of Agder (Norway), but my background – both BA and MA – is in Philosophy of Science (universities of Turin and Florence).

---

Publications

• Seeber M., Cattaneo M., Debernardi C., Pina D. G. (2025). The effect of public funding on long-term relocation of experienced researchers: An analysis of the Marie Curie Career Integration Grant. Quantitative Science Studies. https://doi.org/10.1162/qss_a_00350

• Debernardi C. (2025). A Multilevel Exploration of Science Dynamics with Computational and Quantitative Techniques (Doctoral dissertation). University of Agder. https://hdl.handle.net/11250/3173308

• Debernardi C., Seeber M., Cattaneo M. (2024). Thirty years of climate change research: A fine-grained analysis of geographical specialization. Environmental Science & Policy. https://doi.org/10.1016/j.envsci.2023.103663

• Renzini F., Debernardi C., Bianchi F., Cremonini M. & Squazzoni F. (2023). The New Frontiers of Social Simulation in the Data Science Era: An Introduction to the Proceedings. Advances in Social Simulation. https://doi.org/10.1007/978-3-031-34920-1_1

• Debernardi C., Priori E., & Viola M. (2020). Reclutamento accademico: come tutelare il pluralismo epistemico? Un modello di simulazione ad agenti. Sistemi Intelligenti. https://doi.org/10.1422/97367 - Preprint